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In contrast to the traditional hard thresholding, the coefficients in the finest scale is estimated using Bilateral Filtering (BF). The proposed filtering approach in the finest scale exhibits better connectedness among the edges, while removing the granular artifacts in the denoised image due to hard thresholding. Finally, the use of Guided Image Filter (GIF) on the Curvelet-based reconstructed image (initial denoised image in spatial domain) ensures the preservation of small image information with sharper edges and textures detail in the final denoised image. The lower noise sensitivity of Curvelet phase at higher noise strength accelerates the performance of proposed method over several state-of-the-art techniques and provides comparable outcome at lower noise levels.<\/jats:p>","DOI":"10.1142\/s0219467821500492","type":"journal-article","created":{"date-parts":[[2021,3,9]],"date-time":"2021-03-09T09:56:21Z","timestamp":1615283781000},"source":"Crossref","is-referenced-by-count":6,"title":["Joint Bilateral Filter for Signal Recovery from Phase Preserved Curvelet Coefficients for Image Denoising"],"prefix":"10.1142","volume":"21","author":[{"given":"Susant Kumar","family":"Panigrahi","sequence":"first","affiliation":[{"name":"School of Electrical & Electronics Engineering, Vellor Institute of Technology (VIT), Bhopal, Madhya Pradesh 466114, India"}]},{"given":"Supratim","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Institute of Technology, Rourkela, Odisha 769008, India"}]}],"member":"219","published-online":{"date-parts":[[2021,3,8]]},"reference":[{"key":"S0219467821500492BIB001","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/81.3.425"},{"key":"S0219467821500492BIB002","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.2517-6161.1995.tb02032.x","volume":"1995","author":"Donoho D. 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